Digg, a social networking site (with emergent properties, maybe), has linked to a page boasting a set of sort algorithms faster than Quicksort. It's called Critticall, and it uses genetic algorithms to evolve C programs.

As per Doug's request, here's my revision of Doug's emergence demo code. It's pretty simple. I added a second class, the same as his but with some adjustment in the fitness function to try to account for letters correct in a row. I marked the lines I added so I could later identify my changes. I also added three variables: trials (to indicate the number of trials to be run - and to make it easier to fiddle) and old & new to keep running totals of the number of generations each needed to achieve the correct phrase.

Pandora, as I mentioned in class, is essentially an evolving music website. You enter a song or artist that you enjoy, and Pandora chooses other music that it thinks matches your choice. You can then tell it "no" or "yes" on each song (or you can give no opinion, if you're lazy), and it will modify its choices. I assume that with each answer, the fitness function is modified according to certain variables that a song is assigned. *I have not been paid by anyone to mention this website...but all my friends think it's really cool.

The day I picked out my midterm book, I also came across another of interest that wasn’t on the list - The Quantum and the Lotus by Matthieu Ricard and Trinh Xuan Thuan - and I bought it to read later. My spouse beat me to it and has been pointing out passages from time to time. Last night he showed me one he thought related to our class, and he’s right. I transcribed it below to post for everyone because I thought it was fascinating:

We probably feel the passing of time because of our cerebral activity. Data concerning the external world are transmitted by our sensory organs to our brain, which incorporates them into a mental picture. This cerebral activity brings into play simultaneously several separate regions of the brain with different functions. According to the neurobiologist Fransisco Varela, it’s the complexity of bringing together and integrating these various parts of the brain that gives us the sensation of time. This orchestrated, synchronous activity of large, discrete sets of neurons, among the hundreds of billions in the human brain, creates what scientists call an “emergent” biological state, that is to say a state, in this case the consciousness of time, that is more than the sum of its parts. Since this state lasts from a few tens to a few hundreds of a millisecond, we have the sensation of “now,” of a present with a duration. But this synchronization of neurons is unstable and doesn’t last. Its instability sets off other synchronous groupings of neurons, producing a succession of emergent states. They then give us the sensation of time passing. Each emergent state forks off from the preceding one, so that the previous one is still present in the succeeding one. This gives us the impression that time is continuous. (page 132)

Here is my attempt to better articulate my argument that agent-based models are representable as CAs (which we already know because a Turing machine can be built in Conway's life... but this shows that it's not very complicated to do for a simple agent-based model like Langton's Ant): (also, before the argument, the implication I'm going for--that the distinction between CAs and agent-based models is in fact arbitrary, and although this does not mean that the distinction is not a useful concept, we should recognize its subjectivity) I think that any agent-based model can be represented as a CA.

I modified Paul's last NetLogo program so that the ant doesn't base his moves purely on how successful a bold or safe move has been in the past, but rather on how successful each type of move has been from his current color patch. That is, there is a success ratio for a bold move from a yellow patch, a bold move from a black patch, a safe move from a yellow patch, and a safe move from a black patch. In the clumpier setups, he learns pretty quickly to move safely when on yellow and boldly when on black. Java Applet <

As I was drafting my comment here in response to PG's blog entry, another thought (irrelevant to PG's thread) occurred to me: Is there an agent in a CA? We all know that a defining characteristic of a CA (or an emergent system) is that there is no conductor or director. But what about an agent? What is "doing" a CA? Is the computer the agent? If you read Wolfram's formal definition of a CA, you might begin to think that the rules are the agent. The rules themselves might be the "dynamically interacting rule-based agents" (funny concept there...are CA rules fundamentally "rule-based""?) that are the hallmark of an agent-based model. If so, aren't CAs just a subset of agent-based models?

While paging through Tripod last week in search of a book for the upcoming book review project, I noticed something very interesting: "emergence" is not considered a valid subject, at least in the eyes of the bibliographers who maintain the official Library of Congress subject headings. Even though the books on the suggested reading list all ostensibly represent perspectives on emergence, they are classified under a wide swath of subject headings ranging from "Graph Theory" and "Network Analysis" to "Complexity (Philosophy)" that never include any reference to "emergence." Even Wolfram's A New Kind of Science mentions nothing of emergence in its subject classifications: as far as the Library of Congress is concerned, it is merely a book about cellular automata and computational complexity. Though I know that LC headings frequently fail to capture the full thrust of a book's argument, I think that it's clear that Wolfram's work is about something more than just computation or CA.

So, we've had a taste of cellular automata, and now of agent based models, and are about to go on to other things. Maybe its a good time to look back at our initial thoughts about emergence and what it is/might be good for, and reflect a bit on where we've gotten to so far?

My own thoughts (hoping others will add theirs):

• CA's make interesting patterns, and are fine if one thinks the universe is deterministic and has a lot of time to do the computing needed to predict its future course
• agent based models can make interesting patterns too but also do things that seem more interesting/immediately interpretable to humans

A while back Laura suggested a field trip to The Fabric Workshop and Museum. Next Friday would be an excellent time to go. Shir Ly Camin, Education Coordinator, invites us to: Swarm Conversation with the Guest Curators, Abbott Miller and Ellen Lupton Friday, 3 March 2006 6:00 p.m. Camin says "Miller and Lupton will convene a discussion of "swarming" as it reflects contemporary views of nature, politics, and social life that favor unplanned and decentralized modes of organization. They will be joined by Deborah Gordon, Professor of Biological Sciences, Stanford University and Eugene Thacker, Assistant Professor at the School of Literature, Culture & Communication, Georgia Institute of Technology."